Pursuit of excellence is an integral part of Academics. I had written an article in Times Of India editorial page a few years ago. I am giving that article below. Many years have passed since that article and during this period much more attention has been given to (lack of?) excellence in our country – largely due to the absence of Indian Institutions in the global ranking of universities. There is a stronger desire to have some Institutions globally ranked and respected. As global ranking is largely based on research excellence and impact, there is a need to better understand the reasons behind why excellence often eludes our institutions. I am writing a followup note on this topic – in the process I found that the article I wrote a few years ago is still very relevant. Hence am sharing it here.

♣ ♣ ♣
Think of the names of the best-known scientists in India, and examine their resumes. Inevitably you find that, besides being great scientists and researchers, they were heads, directors or chairpersons of various committees, advisers to ministers/the prime minister, etc. It will be very hard to find a well-known scientist in India who did not become an administrator particularly in the past few decades. (In an exercise we did, a few PhD students were asked to list the Indian scientists whose names they knew and then check their CVs all 21 scientists listed had held significant administrative positions.)

Now let us look at the best researchers in the scientifically advanced countries. Of the 27 Nobel laureates in physics of the last 10 years, only seven hold any major administrative post.

This reflects a basic difference in how science and scientists are viewed in our society and how they view themselves, as compared to the situation in the scientifically advanced countries. We still remain a very hierarchy and title conscious society, where power and title are regarded more important goals than anything else (except money perhaps). When a scientist does good work and is recognised globally, the best way the government and the civic structures seem to reward the person is by giving an administrative title and role, so he becomes a ‘big administrator’ who will rub shoulders with the ‘powers-that-be’. Not only is the thinking of administrators and government like this, this is the nature of thinking of scientists and academics also after an individual has achieved some name in science, he starts looking for ‘elevation’ as an administrator.

We do not seem to have reached a state of evolution in our scientific community where science and research can be ends in themselves, and not a means to a ‘higher’ end. To be fair, a good scientist or a researcher starts with intentions of doing great science/research. However, slowly after a decade or two, often he starts facing the ‘what next’ question. Rather than striving harder to reach a higher level in science and research, either due to complacency which over the years sets in as it is systematically encouraged, or due to lack of recognition or visibility as compared to administrators, or some other reason, remaining a scientist no longer seems sufficient. The senior scientist then starts aspiring for administrative positions with power.

This situation is not likely to change unless there is pride and satisfaction in being an academic or a researcher, and unless there are icons in society that are academics and researchers. In the last two decades, people like founders of companies such as Infosys have created new icons. This has put entrepreneurs and business people on a high pedestal you can see that they no longer feel ‘below’ the bureaucracy but treat them, and are treated as, equal (or sometimes even superior as they are rich).

Similar icons need to be created in academics scientists who are held in high esteem and are ‘stars’ not for the position they hold but for the science and academics they did and contributions they made to the furthering of science, research and education. And the way the government should support them is by giving them labs and grants, awards, monetary rewards, naming buildings, roads and the like after them, promoting them in national and global forums as icons, etc, and not merely by giving them administrative posts.

The management of scientific and academic institutions also needs to change. They have to imbibe the value system where an administrator feels pride in what scientists and academics have done rather than what he as an individual has achieved. And instead of feeling dwarfed by the fame of a scientist working ‘under’ him, an administrator ought to see that as a sign of his doing a good job that should be rewarded.

Unless we reach a stage where the stars are the scientists, and the administrators are understood to be good only to the extent they provide support to create such stars, we should not hope for much excellence. Excellence in research cannot be achieved by half-hearted commitment to the pursuit of knowledge. We must develop a value system where a star scientist wishes to remain a scientist and is respected and admired for the science and research he does.

It should, however, be added that a scientific establishment, if it is to achieve any levels of excellence, must be headed by a scientist/academic of decent calibre who understands excellence and what is needed for it. Putting an average scientist/academic or a bureaucrat in charge can be a recipe for disaster, as such a person is likely to surround himself with average people (“An A hires an A, but a B hires a C”). But the administrator must support the value system in which he is mostly a facilitator for getting good science and research done. The limelight rightfully belongs to the brilliant scientists and researchers doing excellent work.

The traditional model of engineering education for decades has been that in the first year physics, chemistry, and maths are taught as foundation courses. Then courses on different foundational areas of the discipline and engineering are taught. Only after that a student can try to practice engineering. The overall model has been to teach the foundations in the initial years, and only in final year the students may do full engineering projects in which they may build some systems. (Actually, in most cases, unfortunately even in final years decent engineering projects are not done.)

This model has been under challenge for some time, particularly in the west, as it does not allow students to experience the excitement of engineering, which comes from building useful systems that work, till very late. To address this, many institutions across the world have introduced project-based courses early to provide students some experience of building systems.

In IIIT-Delhi, very early we introduced two courses in the first year whose focus is on “hands on experience”. In the first semester, students do a course called “System Management” in which they work with laptops and mobile phones and their components, and learn what they can do with these machines, how they can manage them well, explore internals by opening them and seeing inside, etc.

In the second semester (by when they have learned programming as well as electronics in their first semester) we introduced an Intro to Engineering Design (IED) course, whose basic goal was to design a working physical system that included hardware and software (so software only projects are not permitted) to solve some problem. In IED the focus is on project – the lectures are to support the projects. So, the lectures provide an overview of the basic components that are widely used in such projects – a cheap but versatile platform like RasPI or Arduino, common sensors for vision, motion, proximity, etc, and some actuators like stepper motors, etc. They also learn a bit about workshop and tools.

Students form teams and start thinking about the project from the start of the semester. Each project team is given a budget to buy the components for their project – this exposes them to the process of buying components and markets, as well as about the basic engineering principle of cost control and delivering the project within budget. The completed projects are then demoed to all in an open house one day at the end of the semester.

This year also I visited the demos and interacted with at least 25 project groups. The course instructor was Alexander Fell, who is himself a fine system builder. I was amazed and highly impressed at the sophistication of the projects students had executed. Many of them were better than the final year projects in many engineering colleges and some of them, with extension and further development, could even be the final year project in IIIT-Delhi or an IIT.

To give a sense of the variety and complexity of projects undertaken, I am giving below a brief description of a few projects (I will keep adding to this list). It is worth remembering that these projects were executed by 2nd semester students (i.e. they have been out of class XII only for a few months), who were doing 4 other courses (at least two of them have their own programming/ lab assignments.)

These type of courses emphasize the fact that engineering is about solving problems of people by building systems and solutions using science, mathematics, and theories. Engineering is clearly not about theoretical understanding only in which problems are only solved on paper and tested in exams, or simple labs with defined experiments that are being repeated by students year after year.

Unfortunately, this is what engineering education in the country has degenerated to – most engineering institutions teach concepts (and that too not too well) with almost no exposure to actual engineering – mostly because the faculty does not have the necessary skills to guide such projects. As a result, we find engineering graduates who don’t have any real engineering or problem solving skills and are therefore not employable. And so a large number of these graduates proceed to do MBA where engineering skills are not important, and only conceptual understanding is needed to solve the problems in entrance tests.

This lacuna in engineering education is also contributing to the immature innovation-led ecosystem in our country to generate businesses offering new products and solutions. It has also led to an underdeveloped engineering industry. Thankfully, one is now seeing some examples of innovation resulting from deep understanding of the problem and technology and delivering solutions that can work to solve problems and scale – these are often led by teams that excel in engineering capabilities. Thankfully also, some leading engineering institutions including some IITs (e.g. IIT Delhi) are introducing project based courses early in their curriculum. These bode well for the future for engineering in the country.

Brief Description of Some of the Projects

GardenBot. This bot is essentially a mobile cart with water, mechanical arm, camera, ultrasonic sensor, etc. It moves freely (choses the direction randomly), detects an object and if the object is a plant (done using image recognition library), checks the moisture of the pot, and adds water to the pot plant if the moisture content of the soil is low. It is integrated with the internet to check whether it has rained in the past few days to make a smarter decision for watering. As it moves autonomously, it can water all the pots in a garden – essentially doing the job of a smart gardner.

SmartMirror. It’s a smart assistant (like siri) which you can put on your wall and it looks like a mirror. It’s powered by a Raspberry PI, and has a monitor with a one-way mirror sheet on it so it looks like a mirror on which things can be superimposed / projected also. User interacts with voice commands to get news, maps, etc., which the mirror intelligently displays by getting the information from internet using API calls.

Components: Mic, Camera (presence detection), a flat monitor (with one way mirror sheet posted on it), Speakers; a case was made to hold all components and make the monitor look like a mirror.

Faux Arm. A robotic arm that wirelessly mimics the arm movement of the operator. The Faux Arm is a robotic arm with three points of movement, simulating the operator’s elbow joint, wrist joint and two fingers for grabbing and picking things up. We also built the Sensor Sleeve, a sleeve with sensors that can be worn by the operator on his/her arm, serving as a wireless input to the robotic arm.

Robotic humanoid hand. In our project we had constructed a robotic humanoid hand. The 3D model of hand was open source and easily available on Inmoov. Our project used 3 types of control functions i.e. glove control using flex sensors for remote control of the robot, voice commands using the voice sensors, and direct muscle controls using the myoware muscle sensors. This hand can be used by amputees and physically challenged (using muscle sensor or voice control), for exploring inhospitable areas (by glove or voice control), etc.

ShadowBot. Despite the technology today, large parts of the world remain inaccessible due to the inability of the humans to survive in harsh conditions. This can be changed by using robots. However, AI is not yet developed enough to allow robots to react accurately in delicate situations. Our project aims to improve the ability of a human to control a robot, by allowing it to mimic the user’s actions! Project Demo on YouTube.

Sensors: Microsoft Kinect v1.8

Actuators: S3003 Futaba Servos (ten for different joints and degrees of freedom);

Ambhibian BOT: It is a remotely controlled (through the Ardiuno RC controller, configured for Bluetooth) amphibian robot which has the capability to travel through varied tough terrains, including water bodies (antenna and camera remain outside the water), to provide video feed. It comes with an emergency propeller which can be used in case the directional motors fail. Entire functionality is controlled via Bluetooth connectivity, and a live video feed is given by the camera attached at level height of the robot to the phone.

DrawBot. An automated arm that drew pictures given to it with a pen on a paper. The input was an image file. From the grey scale image of the file, we extracted edges and lines (using Sobel edge detection algorithm) in the picture, and then drew these lines using the DrawBot arm. For drawing, movement was controlled by two stepper motors. The Drawbot worked by making use of the nearest salesman algorithm that moved the arm in the direction of nearest pixel, by drawing small segments of lines using the slope and coordinates.

SmartCart: We made an automated cart which follows the user based on a tag which the user wears. When placing the product in the cart, the product’s barcode is scanned and the bill prepared automatically in the app on the mobile phone. By using such a cart, a store owners can reduce their manpower for checkout, and also reduce the waiting times for customers.

Platform and Code: Arduino, Android phone. About 90 lines of C code, and about 640 lines of Java code (for the App), about 200 LOC of PHP on the server (mimicking the inventory of the store).

Team: Aakash Sehrawat, Anmol Prasad, Nilay Sanghvi, Saksham Vohra

Plant Watering System. This project provides water (which may contain other essential nutrients) to multiple plants based on their respective moisture sensor readings. The frequency to check the moisture reading depends on the temperature and humidity readings given by the temperature sensor. A GSM module timely informs the owner through SMS about the water level of the tank, and when the plants are watered. (A few teams did project of this type).

Autonomy of higher educational institutions/universities (HEIs) is now widely acknowledged as a necessity for excellence and improvement, particularly for those HEIs that engage in research as well as education. In India we hear about the need for more autonomy in newspapers and debates. Most discussions and articles talk about autonomy as a broad concept and its desirability or how it can help improve the level of education and research. What specifically needs to be done to improve autonomy is rarely discussed. This note discusses a few issues, which I believe are most important for autonomy of our HEIs, and without which autonomy, and therefore aspiration for excellence, will not come about.

Recognizing the importance of autonomy in HEIs, the EU had started an autonomy scorecard for its member countries. The framework for autonomy had these four key dimensions:

Academic

Organizational

Financial

Staffing

Academic autonomy has been sometimes in the news, largely due to the requirements imposed by key regulators (UGC and AICTE) on the HEIs. While it is important, I believe, that many Act created HEIs (e.g. IITs, IIMs, IIITs, many Universities etc.) can exercise due control in this sphere. In any case, it is a topic for discussion on its own. (Perhaps a future note will discuss this.) in this note I will focus on two fundamental issues in Organizational and Financial dimensions.

First issue relates to the organizational dimension. Organizational autonomy starts with how autonomous are the HEIs in appointing their Chief Executive – i.e. the Director or the Vice Chancellor. This is the most important aspect of Organizational autonomy, as it impacts all other organizational issues. In most western countries, this selection is generally done by the bodies of the university – the Board, Senate, a Board of Trustees appointed search committee, etc. (though the selection may sometimes be subject to approval, which is usually a formality).

In our country, the Chief Executive is selected by the Government or the Ministry, though there is generally a selection committee to recommend a set of names from which the final choice is made. If the final decision of the Head of the Institution is left to the Government, the same person(s) will be doing the selection for all the HEIs of the state/center. Hence, it may be perceived by potential candidates that being in the “good books” of the person(s) is important. This creates distortions – from some good candidates not applying to some lobbying for posts. This has created a general perception that factors other than merit influence these decisions.

Suppose each HEI was to select its own Chief Executive through a documented and transparent process that involves the stakeholders from the HEI, as is done in many countries. With selections/appointments distributed, there is no single authority that needs to be convinced, thereby giving candidates multiple opportunities of assessment by committees of different HEIS. Furthermore, in selection by a single authority, the selected person is more indebted to that authority rather than the HEI for selection. If the HEI was to select the Chief Executive using its stakeholders, then the answerability of the Chief Executive is naturally to the HEI and its stakeholders.

This single change of having each HEI select its own Head through an approved and open process can bring about a great deal of autonomy in our HEIs. Thankfully, the authorities seem to appreciate this and there are signs that this is beginning to happen – one hears that in the IIM Bill, this autonomy has been granted. Hopefully, as a next step, this change will be made for institutions like IITs, and reputed Central Universities.

The second main area in need for autonomy is financial. As long as there is financial dependence of HEIs on the government, autonomy will always be compromised. Yet, public HEIs need support from the government, to provide affordable education to citizens. So, how can one achieve autonomy while still seeking public funds. A simple method, which now many countries use, is to have the funding be based on some parameters by applying some formula. E.g. funding may depend on the total number of students, faculty, R&D projects, consultancy, etc, and the support level is decided through a defined formula. Given that different HEIs have evolved in different manner and may have different needs, the formula need not be same for all types of HEIs. For example, a business school may be given little or no support for education, while an Engineering Institution may be provided limited support per student for education, and a humanities oriented institution may be provided a higher level of support per student.

A formula based funding makes the HEI “independent” of its equations with the Government of the day. The formula provides predictability of funding, and the HEI can count on it and focus its energies on its academics and more efficient use of this public funding. This enhances the autonomy of HEI autonomous, while still retaining the public character.

While these can improve the autonomy of HEIs substantially, there is a need to also ensure that HEIs, particularly those who are taking public funds, are discharging their responsibilities to the society properly.

How does one ensure accountability? This is important as without this, autonomy can lead to inward looking HEIs which are not responsive to societal needs. The responsibility of an HEI is mostly around expanding its educational opportunities, and to align its research towards national goals or needs. (Responsibility in terms of access is already built-in through reservation laws.) Both of these can be easily achieved through financial models. E.g. if funding is tied to the number of students studying (as is the case in Australia), then there is an incentive for the HEI to increase its student strength. Similarly, research direction is often influenced by providing research projects and grants in specific areas/types of work – an approach taken by most countries, including India.

With organizational autonomy, there is also a need for internal systems of the HEI to have proper checks and balances. For this, it is imperative that the system being followed is where the approving authority is different than the recommending authority. This is most important in faculty appointments – if these appointments are not done properly and with rigorous processes, it can lead to substandard faculty, which takes an HEI down a path from which it takes decades to recover, as faculty stay in the system for even three decades. For this, the system followed in institutions like IITs is very sound – the recommendation for faculty selection is made by a selection committee which is chaired by the Director. But the recommendations are accepted by the Chairman of the Board on behalf of the Board of Governors. However, an alternate method, which is seriously flawed, is also followed in many universities in India, in which the Vice Chancellor chairs the selection committee, as well as the Board of the University, thereby making the recommending and approving authority as the same. This must be corrected to ensure that the autonomy does not get misused.

There are many factors that impact autonomy, many of them not covered in this note. This note focused on two most important issues for autonomy: (1) the selection of the Chief Executive should be done by the HEI itself through transparent and well defined process that takes inputs from the stakeholders of HEI, and (ii) funding of each HEI should be formula-based dependent on some important parameters like R&D output, number of students, etc. so the HEI is clear about what level of support to expect. If these two can be done, we can possibly see an unleashing of trapped energy in some of the HEIs which can take them to path of excellence and global ranking/standing.

Recently it was reported in newspapers that CBSE moderates its marks by effectively increasing them – largely to “compete” with other Boards. It was also reported recently that some of the top colleges in Delhi have a majority of students from one Board in south, and a large number from one school.

Both of these anomalies are due to one reason – admission being based on Board percentage without normalizing the marks of different Boards. Due to this, Boards realize that their students will benefit if they have a higher percentage – so there is a race to give more marks. Besides distorting the admission process, this race is unhealthy for education and learning and gives a false sense of achievement to students.

Of course the natural course of action is to normalize marks from different Boards. Normalization across Boards can be easily done – all it requires is a little extra information from each Board. For some strange reason, it has not become regular practice and Boards do not provide sufficient information for normalization.

Let us first understand the normalization problem. Each Board gives marks between 0-100%. Normalization requires that marks between 0-100 given by different Boards be converted to a “normalized score”, also between 0 and 100, which provides a common reference where X marks mean the same, regardless of whether the Board was “tough” or “easy” in its marking.

One approach to normalize, which CBSE also used for JEE, is to base it on the percentile of a student in the Board. The percentile score of a student reflects what percentage of students in the Board have marks below that of the student. I.e. a student with 90 percentile means that 90% of the students have received marks that are below this student’s marks. To convert marks to percentile score, students are ordered in the order of marks they received, and then divided in 100 equal groups – the top 1% students fall in 99-percentile, the next 1% fall in 98-percentile, etc. (This can, of course, be done at 0.1 or 0.01 percentile granularity for finer resolution.) Once percentile is given, then there are ways to normalize, with the assumption that top N% of the students in a Board are essentially similar to top N% students in another Board, i.e., a 99 percentile student in one Board can be considered similar to a 99 percentile student of another Board. (If this assumption cannot be made, then it will require calibrating different Boards – an exercise that is unlikely to be undertaken, and if initiated, unlikely to culminate in an acceptable calibration.)

With a percentile score, one way to normalize across Boards is simply to use the percentile score. In this case, a student with 99.5 percentile (from any Board) will be ranked higher than a student in 99.3 percentile (from any Board). The percentile score can have finer granularity, if desired, and within each percentile, there can be tie-breaking rule.

The ranking with percentile is sufficient if the decision of admission is based only on class XII score, i.e. one needs to rank or order students only on class XII score. However, if admission is based on sum of multiple scores, in which one of them is the class XII marks (as was the case in JEE, where 60 marks came from JEE exam and 40 from class XII), then the situation is more complex and percentile will have to converted to a normalized score to be added to the other scores.

There are techniques to convert the percentile score to a normalized score. For this conversion, a desired target distribution is needed, which gives what fraction of students should be at each mark in the normalized marks between 0-100. The target distribution for normalized marks is a choice to be made, and any reasonable distribution can be chosen – the preferred distribution for exams is Normal Distribution, in which the largest fraction of students is at the mean and then the fraction at each mark reduces as we move on the two sides of the mean. If the target distribution is taken to be Normal Distribution with mean of 50 and the standard deviation (a statistical attribute indicating the variability in scores) of 15, then 99 percentile will translate to 85 normalized marks, 98 percentile to 81 marks, 95 percentile to 75 marks, 90 percentile to 69 marks. There are standard tables available for this conversion. (This conversion will be different if a different mean and/or standard deviation are selected.)

It should be clear that with percentile based normalization, inflating marks in a board does not help students – the top 1 % students of all boards will be mapped to the same normalized marks. So, in a Board which has inflated marks such that a large fraction of its students get above 90% marks, only the top 1% students will get the same normalized score (99 percentile, or 85 marks in the above example), which will be same as the top 1% students from a Board which has a much smaller fraction of students above 90%.

Overall, normalization can be done easily and transparently if information about percentile of a student is provided by the Boards. If Boards provide the percentile, normalization is straightforward.

Normalization is not possible if Boards only give the percentage marks to students, as they do now. Though determining percentile is trivial and Boards can easily do it, for some reason, it is not being done. Perhaps because just with marks a Board can have as many students above 90% as it wants and let the students and their parents feel good. With percentile only 10% of the students can be in the 90 percentile – which will give a clear picture to the student about his/her relative standing in the Board. Given this situation, probably MHRD will have to mandate that percentile information must also be provided to the students. And to support this move, all universities that use class XII marks for admission can declare that they will normalize marks of different Boards and will therefore not admit students from a Board unless the percentile scores are also made available – if this is done all Boards will have to provide this information.

If normalization is done, besides fairness in admissions, it will also lead to curtailing of the unhealthy exercise of marks inflation that the boards seem to have gotten into. If normalization is not done, given the publicity received about DU’s admission this year, we will see an unhealthy race between Boards to give easy marks, resulting in a complete failure of merit based admissions, with less deserving students from some Boards getting admission into the best colleges in the country at the cost of more deserving students from some other Boards being denied admission.

It is well established that good quality higher education is the best way to open doors to a variety of opportunities – that is why world over students vie to get into the best universities and colleges. Due to this, while school education is meant to lay the foundation for a broad development of the individual, the single most important goal of school education becomes getting admission in a high quality higher education institutions (HEI).

Admission to our HEIs is based almost exclusively on performance in exams – class XII or entrance test. Most engineering institutes admit students through entrance test, though now class XII marks are also given weight, and most universities like Delhi University give admission based on class XII marks (though have some seats for sports etc). So, regardless of what educationists may like to see, students, parents, and teachers all eventually align to a single goal as outcome of school education – doing well in class XII exams and competitive entrance tests. As nothing else matters for achieving the important goal of getting into a high quality HEI, other aspects of development that the school education is supposed to provide, are mostly ignored.

As a result of this exclusive focus on exams, a student who does innovative projects in schools demonstrating innate talent and interest for engineering is precisely the one who may not make it to the best engineering institutions as he/she “wasted” time doing these projects – time which could have been more optimally used in coaching classes. Similarly, a student who does internship in some company and writes a report on the economics of a sector – perhaps the ideal candidate for an economics program – may not be able to get into a good economics program as others who spent all the time preparing for exams get higher marks. Similarly, students who engage in school debates, participate in social work, sports, or other activities that can broaden their development and horizons, are often at a disadvantage for getting admitted to HEIs as compared to those who spend their time preparing for tests. This uni-focus on attaining high test scores also inevitably leads to shallow learning styles which maximize performance in tests but prevent deep understanding of subjects.

This focus on exams cannot be changed just by exhortation or changing the pattern of the exam or bemoaning the state of affairs. We have to squarely accept the fact that the most important goal for a student is indeed getting admission into best colleges, and if we want students to have wider development in schools, we have to widen the criteria for admission to include achievements and efforts outside tests.

One direct approach can be to assign some marks (say 20 out of 100) for achievement in other spheres while the remaining 80 can remain based on results of class XII and entrance test. With this, the problem reduces to developing sound procedures for assigning marks out of 20 for achievement in other spheres. This will be a challenge but not one that is unsurmountable – PG/MBA programs or public service exams routinely do this, by having an interview and assigning some weight to it.

IIIT-Delhi has been following another approach for the last few years for this. In IIIT-Delhi, for admission in BTech program, up to 10 bonus marks (on a base of 100) are given for achievements in various spheres, through a published criteria. For example, bonus marks are given to students who reach final stages of various Olympiads, participate in national school games, have Chess FIDE rating, get an award in the INSPIRE or IGNITE program, win prize in programming contests, have ministry of culture’s scholarship for talent, etc. The program was slow to start, but in the previous two batches, over 10% of the students admitted are ones who have received bonus marks.

We have also done some analysis of how these students perform in our Institute. As we had anticipated, the first year performance in the Institute of the students who had received bonus marks was significantly better than the performance of students without bonus marks (the average CGPA was higher by more than 1.) This clearly demonstrated that students with broader base are likely to be better prepared for higher education.

Most US universities, while giving a considerable weight to SAT scores and performance in high school, consider a host of other factors and achievements for admission. In fact, in top universities it is now known that just good grades and SAT scores are not sufficient, and students must show other achievements. This hugely motivates families to develop other aspects of a students’ personality – sports, culture, social work, volunteering, etc. If we start incorporating achievements and contributions in other spheres in admission to most of our top HEIs, we may also see an increase in motivation and drive to undertake such activities in school – this can only be good for our students and their development.

Many faculty have observed that often performance of students in later years of a 4-year program is similar to the performance achieved in the first year. At IIIT-Delhi we did some analysis of student performance in the Institute in various years and relationship between them. IIIT-Delhi has a rigorous and demanding education program, as good as the best in the country, and taught by faculty with qualifications similar to those of faculty in established IITs. Its program, though somewhat different and more innovative than in older institutions, is similar to the programs in IITs and top universities across the world – it has a common first year program, core courses for the discipline done in a few semesters after the first year, and mostly electives in final few semesters. Therefore, I suspect the trends in our analysis may hold for other similar autonomous institutions which have high quality education. Some interesting findings are:

Correlation between performance in first semester and second semester is over 0.8. In other words, for most students, performance in second semester is similar to the performance in the first semester.

The performance in an academic year is very strongly correlated with performance in the previous academic year – again correlation of more than 0.8. In other words, performance in 2nd year has a strong correlation with performance in 1st , 3rd year performance is highly correlated with 2nd, and 4th year performance is highly correlated with the 3rd.

Before discussing what these correlations may mean, it should be emphasised that these are statistics – they apply in a general sense and not to an individual. An individual student’s record may not follow the above pattern at all – someone may have had a bad 1st semester/year (due to illness, lack of seriousness,…) who can do much better later. And someone who takes first year seriously and then slacks off, will find performance falling.

What do these mean for students in a general sense. The data seems to suggest that the first semester and year can often be the most defining year of a students’ college education, and the performance in first year often reflects the level at which the student is likely to perform academically in the rest of his/her program. First year of the program is when the students are settling in their new life at a university/college with the freedom and responsibility that comes with it – a life very different from that in school which is far more structured and defined by the teachers, school discipline, uniform, parental oversight, etc. It seems that the students define their approach to college life and academics in the first year and often develop habits, discipline, and balance (or lack of it) which is likely to stay with them for the rest of the program.

As mentioned, while the data suggests this for most student, it need not apply to all students. If a student misses building the discipline and balance in the first year, but realises the folly of his/her ways later (say after a semester or a year), this data should be treated as a statistic that can be overcome – by putting the due effort for making up for the lack of effort in the first sem/year, or by repeating the first year, if the university allows. (In IIIT-Delhi students who do not pass some number of courses in the first year have to repeat the first year. In the past we have seen that there are some cases of students who have changed their behavior after repeating the year and have successfully completed the program with good CGPA.)

What does the data mean for academic institutions and administrators? One clear insight is that first semester (and the first year) can be extremely critical to a student’s success in the program. Therefore, to help students succeed in the program, it is important to provide good support to them in their first semester (year) – not just for academics but also for developing good habits and discipline. This implies that the systems we have for later year students, may not be well suited for students in their first year, who require closer monitoring and more support and counselling.

To conclude, data suggests that incoming students should be extra cautious and alert when starting their higher education program – while a student must explore new ideas, build new bonds, try new activities, pursue non-academic interests, engage in deep discussions in the canteen, etc, he/she must not lose sight of academics, as that is the primary purpose of entering a university. Students must develop sound habits and a good discipline and balance in their first year – the habits and discipline developed in first year is likely to persist through the rest of their program; laxity in the first year may make it harder to make up in later years.

And for Institutions the data clearly suggests that special measures must be taken to handle students in their first year – they are just transitioning from school to college and support must be provided so they can develop a proper balance and discipline to handle college life. (At IIIT-Delhi, a few years ago we started a one-week induction program for the new students where issues like this are discussed with them by counselors, senior students, and other professionals. And we have started a program of monitoring first year students more carefully in the key courses and provide extra support where needed.)

This is admission time again for higher education, and most students have multiple choices of higher educational institutions (HEIs – colleges, universities, institutes) for admission. Finally, of course, the student has to get admitted in one HEI and study there. For most students and their parents, this is a hard choice – which HEI to chose from the colleges, universities, institutions where the student can get admitted. This note points out some parameters that can be used for assessing an HEI (or a department).

First, let us understand that there are two main end goals of college education. (i) Education: gaining knowledge and skills for productive careers, and (ii) Self growth: developing interests, friendships, associations, hobbies, etc which help in leading a happier and richer life. A high quality HEI should provide good support for both.

For assessing the capability of the HEIs, or one of its departments, to deliver high quality education, there are some well understood parameters. I am giving some of the key ones here. These are the parameters which I advise parents and students to look at for making a decision, and I myself used them when my daughters were seeking admission. Importance of most of these is self evident, and many of these are also given in the World Bank framework for World Class Universities.

Faculty Quality and Qualifications. This is undoubtedly the single most important parameter that decides the quality of education in an HEI. World over, the best Universities indeed have the most qualified faculty. In India also, you will see the same pattern – places like IITs, IISc, some IIITs, some ISERs, etc, which are known to be the best places for education, have the most qualified faculty. By qualifications of faculty I mean – highest degree obtained (PhD, Masters, or lesser), and from where the degree was earned. While higher qualifications are clearly desired in faculty, the second factor is also very important – an Engineering institute that has faculty with PhDs from reputed universities of the world, or from places like IITs/IISc, clearly has superior faculty than a college that may have PhDs from other institutions. This can be checked easily – see where the faculty of established IITs have obtained their PhDs from – you will see that they are from top Institutes in the country, or from good institutions overseas.

Faculty Student Ratio. This is clearly the next important parameter – an HEI which has lower F/S ratio is likely to be better for learning and education, as it allows more faculty time per student and only with manageable ratio can faculty spend time with students for projects etc. In many US universities, about 20:1 is a standard ratio that they try to maintain – some lower ranked universities may have ratios as high as 35:1 or more, and some of the Ivy League and other top univs may have lower ratios. In older IITs, the ratio is about 15:1.

Infrastructure. The quality of infrastructure is another important parameter – clearly for education delivery, quality of classes, libraries, labs, etc. is important. But even other infrastructure – facilities for faculty, quality of student hostels and facilities, quality of sports and other facilities for extra curricular activities, etc. matter as they have indirect impact on education.

Quality of the academic program. All good HEIs spend a lot of time designing their programs. First important factor here is the structure and layout of the program – the courses the program and the nature and variety, and the degree of flexibility it provides to students to chose their courses. The second aspect is very important and can be assessed by the number of electives a student can take in the program and the number of choices offered for electives. Weaker HEIs will have fewer electives, and fewer choices for them, as electives require a larger range of courses to be taught.

Delivery of academics. Getting a good program on paper is not too hard – programs of the best of HEIs are available on the internet. It is, of course, the delivery of the program that matters the most. Quality of delivery is decided, first and foremost, by the quality of faculty. However, there are some other indicators – e.g. the level and nature of work a student has to do in the courses. If the student has to spend minimal effort and that is mostly around taking tests/exams, you can be sure that the delivery of courses is weak. Good delivery of courses requires students to put in effort outside the class in assignments, projects, labs, term papers, presentations, etc. Learning happens largely when students are asked to apply the concepts covered in lectures in the assignments/labs/projects… Learning without due effort is a myth – effort and practice is essential for learning and developing skills.

Administration, leadership, culture. Administration and leadership impact the overall functioning hugely – good administration and leadership will ensure that the HEI continues to improve and keep addressing issues that may come up. Seriousness with which academics is taken, how students are supported, are students’ feedback on programs and courses taken, etc. are all important cultural aspects that have impact on the quality of education.

For assessing the quality of an HEI for supporting self development, one should look at the breadth and flexibility in the curriculum – does the curriculum include courses other than main subject courses, and does it provide flexibility and choice to take a variety of courses including those that may help more in self development. For example, one can look at if there are course on humanities, social sciences, music, art, etc, and if it is possible for students to do independent study, independent projects, etc to pursue their interests. For students who may be interested in research, one should look at if there are provisions for UG students to undertake research.

Other important factors that affect the self growth dimension are the level of extra curricular activities (which may get reflected in the variety of student clubs), infrastructure (the quality of infrastructure to support the extra curricular activities) and support (e.g. is there sufficient budget) for such activities.

While these are main factors that affect the quality of education, another way to assess the quality of education and overall development of students is to examine what the graduates of the HEI do after graduation, and how well the alumni of the HEI are doing. Opportunities after graduation include – placements after graduation (quality of placements, median offer, etc), higher education opportunities (how many students get these opportunities and where), and entrepreneurship.

This note focuses only on assessing the quality of an HEI. Choosing a program to study is a different issue – it depends on the students aptitude and capability. In an earlier note, I had discussed this issue. Of course the complication comes when the two factors – choosing the HEI and the program of study – are combined. The most common question is “I am getting X in A but am getting Y in B – which option should I choose”. In general, if one is sure that one wants to study X and is fairly sure that he/she has the aptitude for it also, then I would say that find the best HEI you can get X in, and go study X in that HEI. The problem gets more complex when the student does not know what he/she is interested in or has aptitude for – I have discussed this briefly in my earlier note, though have no good advise to offer.

Finally, I would end by saying that choosing the HEI for your college education is a serious decision, and a lot of people try to influence it – mostly to try to convince others about their own view/decision. I have had students write later “I was misguided and I took admission in A as many of my friends were taking…. but I find no academic atmosphere here …. can you please consider me for admission now….”. You don’t want to be in this situation. So, I suggest that you take inputs from all – your parents, friends, teachers, experts – but be aware of the biases that are often there in such suggestions, and make up your own decision by doing your analysis of the information/data available.